Engaging Two-Eyed Seeing to enhance regenerative tourism
Bibliographic record
Abstract
Recent critiques in the regenerative tourism scholarship have pointed to the limited engagement with Indigenous ways of being, recognizing that Western paradigms alone may be incongruent with advancing regenerative outcomes. As such, a response has been called to intentionally engage with Indigenous Worldviews and Knowledge Systems. With participants ranging in age from 9 to 92, the Grand River Community Play Project (GRCPP) invites communities along the river to refamiliarize themselves with diverse and complex histories of place through art and storytelling. The aim of this intrinsic case study is to illuminate how the GRCPP engages with Indigenous Knowledge Systems and thus responds to recent calls to address the gaps in regenerative tourism scholarship. Guided by Etuaptmumk or Two-Eyed Seeing and inspired by Creative Analytic Practice, the authors share two vignettes to illustrate how the GRCPP incorporates transformative learning (knowing), experiencing place (being), and regenerative action (doing) in its praxis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.015 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".